Sara Wade

Reader in Statistics and Data Science

Curriculum vitae

[email protected]

School of Mathematics

University of Edinburgh

Room 5406
James Clerk Maxwell Building, Edinburgh, EH9 3FD


Leveraging variational autoencoders for multiple data imputation

Breeshey Roskams-Hieter, Jude Wells, Sara Wade

Proceedings of the European Conference on Machine Learning (ECML-PKDD) 2023, Springer Lecture Notes in Computer Science

Fast deep mixtures of Gaussian process experts

C. Etienam, K. Law, S. Wade, V. Zankin

Machine Learning (to appear), Springer, 2023

Bayesian cluster analysis

Sara Wade

Phil. Trans. R. Society, vol. 381(20220149), 2023

Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences

A.K. Leist, M. Klee, J.H. Kim, D.H Rehkopf, S.P.A Bordas, G. Muniz-Terrera, S. Wade

Science Advances, 2022

Bayesian nonparametric scalar-on-image regression via Potts-Gibbs random partition models

Mica Teo, Sara Wade

Springer Proceedings in Mathematics and Statistics, New Frontiers in Bayesian Statistics, BAYSM 2021: Selected Contributions, 2022, pp. 45-56

Colombian women's life patterns: A multivariate density regression approach

S. Wade, R. Piccarreta, A. Cremaschi, I. Antoniano Villalobos

Bayesian Analysis, vol. 17, 2022, pp. 405-433

Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data

W. Yu, S. Wade, H.D. Bondell, L. Azizi

Journal of Computational and Graphical Statistics, vol. 32(2), 2022, pp. 588-600

Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models

C. Gadd, S. Wade, A. Shah

Machine Learning, vol. 110, 2021, pp. 1105-1143

Enriched mixtures of Gaussian process experts.

C. Gadd, S. Wade, A. Boukouvalas

Proceedings of Machine Learning Research, International Conference of Artificial Intelligence and Statistics (AISTATS), vol. 108, 2020, pp. 3144-3154

Posterior inference for sparse hierarchical non-stationary models

K. Monterrubio-Gomez, L. Roininen, S. Wade, T. Damoulas, M. Girolami

Computational Statistics & Data Analysis, vol. 148, 2020, pp. 1-22

Bayesian cluster analysis: point estimation and credible balls (with Discussion)

Sara Wade, Zoubin Ghahramani

Bayesian Analysis, vol. 13, International Society for Bayesian Analysis, 2018, pp. 559 -- 626

Prediction of AD dementia by biomarkers following the NIA-AA and IWG diagnostic criteria in MCI patients from three European memory clinics

A. Prestia, A. Caroli, S. Wade, et al.

Alzheimer's & Dementia, vol. 11, 2015, pp. 1191-1120

A Bayesian nonparametric regression model with normalized weights; A study of hippocampal atrophy in Alzheimer's disease

I. Antoniano-Villalobos, S. Wade, S. G. Walker

Journal of American Statistical Association, vol. 109, 2014, pp. 477-490

Alzheimer's disease biomarkers as outcome measures for clinical trials in MCI

A. Caroli, A. Prestia, S. Wade, et al.

Alzheimer's Disease \& Associated Disorders, vol. 29, 2014, pp. 101-109

Improving prediction from Dirichlet process mixtures via enrichment

S. Wade, D.B. Dunson, S. Petrone, L. Trippa

Journal of Machine Learning Research, vol. 15, 2014, pp. 1041-1071

A predictive study of Bayesian nonparametric regression models

S. Wade, S. G. Walker, S. Petrone

Scandinavian Journal of Statistics, vol. 41, 2014, pp. 580-605

An enriched conjugate prior for Bayesian nonparametric inference

S. Wade, S. Mongelluzzo, S. Petrone

Bayesian Analysis, vol. 6, 2011, pp. 1-28


Contributions to Papers with Discussions

Preprints/Submitted Articles

Mixture of Gaussian Process Experts with SMC^2

T. Harkonen, S. Wade, K. Law, L. Roininen



Bayesian Statistics and New Generations: BAYSM 2018, Warwick, UK, July 2-3, Selected Contributions.

Selected Contributors

Springer Proceedings in Mathematics and Statistics, R. Argiento, D. Durante, S. Wade, 2019


Follow this website

You need to create an Owlstown account to follow this website.

Sign up

Already an Owlstown member?

Log in